Speeches by Richard W. FisherNew York City, New York | November 2, 2006

Confessions of a Data DependentRemarks before the New York Association
for Business Economics

I am grateful for your invitation
to speak before the NYABE today. My dear friend of decades
and director of research at the Dallas Fed, Harvey Rosenblum,
was once the president of NABE and spoke to this fine
assemblage of minds back in 2002. That speaks volumes
about the quality and importance of this forum. It is
an honor to appear before you.

In keeping with today's popular
obsession with disclosing any and all personal faults
to as large a public as possible, I have a confession
to make: I am data dependent. I have developed a strong
and growing addiction to ever more refined and pure
economic data. Alas, the stuff I need to feed my habit
is not available on the street. So I am here today to
suggest to you that there might be a profitable market
for clever economists to exploit.

Before I get into that, please
allow me to issue two disclosures. First, the thoughts
I am about to share with you are my own and not those
of any other Federal Reserve official or of the Federal
Open Market Committee. Second, I am not a trained economist
and make no pretense whatsoever of being a formal practitioner
of the dismal science. To me, "dismal" is a misnomer;
economics is a vibrant and exciting field of study,
especially in a capitalist society where it best applies
itself to the conundrums of capital markets and the
intricacies of monetary policy.

I came to economics and the markets
late in life. I started out as a midshipman at the Naval
Academy, then migrated from learning to navigate the
seas to navigating through the undergraduate basics
of economics at Harvard. After a brief detour to Oxford—principally
to find my wife and perfect my taste for good beer—it
was onward to Stanford Business School, where I discovered
what has become a lifelong passion, with its own branch
of economics: decisionmaking under conditions of uncertainty.

For over a decade before I took
up public service in 1997, I was able to profit from
that passion as a hedge fund manager. Back in those
days, the investors in funds actually made more than
the managers of those funds—imagine that! Now
I have the responsibility to apply what I have learned
over the years in a different context—the making
of monetary policy.

Successful hedge fund managers
and effective central bankers share at least one trait:
They abide by what I refer to as "the Gretzky principle."
Hockey's Great One, Wayne Gretzky, once proclaimed,
"I skate to where the puck is going to be, not
to where it has been." It seems to me that success,
whether for central bankers, hedge fund managers or
business economists, comes with anticipating what comes
next and acting decisively to be positioned for where
the economic "puck" is likely to go.

To apply the Gretzky principle,
good judgment, not a small amount of good luck and good
data are needed.

Good judgment certainly characterizes
the men and women I have the honor of serving beside
on the FOMC. For today's purposes, I want to duly note
their good judgment, politely brush aside luck—we
will always take as much as the monetary gods are willing
to grant us—and focus on an essential element
in the art of making fruitful decisions in an uncertain
world: good data.

I hardly need to explain the importance
of good data to any of you. We all know the consequences
of data being wrong or arriving too late. Our reputations
rest on the data we use. The better the data, the less
our uncertainty. And the less our uncertainty, the better
our ability to make sound decisions.

Without a doubt, both the quantity
and quality of the data I review now as a Fed bank president
and FOMC participant are far beyond what I had access
to in the past. The Fed's data resources are unmatched,
as is the interpretation of that data offered by the
exceptional minds of its regional and Washington research
staffs. Yet one can never be satisfied. As good as the
data are, they are never good enough. We have a great
deal of accounting and analytical work left to do as
we seek to refine our ability to make monetary policy
in an increasingly complex world.

Let me give you some examples
of data inadequacy.

To begin with, most economic data
are inherently backward looking, often to a disconcerting
degree. Obviously, there is no way around this. Obtaining
completely accurate forward-looking data would require
extensive investment and research into that other dismal
science, science fiction. Yet time-travel aside, we
must strive to develop reliable real-time data collection
technologies and ever more practicable models based
on the limited framework of historical observations.
That process is ongoing. To paraphrase singer–songwriter
Robert Earl Keen, the road goes on forever and the analytical
party never ends.

This is not to suggest that simply
developing more enhanced models using available data
is all that is needed for us to do our job better. In
a rapidly changing world where microeconomic operators,
enabled by expanding economic geography and technological
innovation, are constantly pushing the envelope of production
and profits, one can never be confident in the insights
provided by even the most sophisticated econometric
models.

Each month, as I prepare for an
FOMC meeting, I spend a great deal of time talking with
CEOs and CFOs of companies to gather their impressions
of the current state of the economy. To prepare for
this last FOMC meeting, for example, I spoke to the
leaders of companies whose annual revenues aggregated
to a little over $1 trillion and whose operating income
easily exceeded $110 billion last year. In these monthly
interviews, I ask about activity and trends in their
businesses and what they see happening with their production
lines, customer bases and competitors in hopes of gaining
insight into current growth and inflation dynamics in
the economy. Recognizing the limits and risks of anecdotal
evidence, even coming from the most disciplined and
experienced corporate operators, I personally find this
an effective way to bridge the gap between what our
economic models tell us—based as they are upon
historical data and various theoretical assumptions
about the future—and what is happening in the
real economy.

During these conversations, I
usually hear a keyboard clicking away in the background
as these CEOs and CFOs punch in a few commands in response
to my inquiries. And presto, accurate data emerge from
their desktops about new orders, inventory levels, capacity
utilization, input prices and a slew of other indicators
that are minutes—not months—old.

To be sure, the ubiquitous nature
of the data available to today's business operators
raises the risk of drowning in information as they search
for knowledge. Nevertheless, a significant disconnect
persists between the instant and accurate data available
to the hands-on operators in the economy and the inadequate
and delayed data our macroeconomists are given to contemplate.

I do not envy the statisticians
charged with tracking the U.S. economy. We are a behemoth—$13
trillion in GDP, 300 million mouths to feed, 140 million
workers, billions of transactions on any given day.
But working with incomplete and belated information
limits our ability to "skate ahead of the puck."
For example, the service sector now represents 70 percent
of the U.S. economy, yet we remain incapable of forecasting
with service-sector data because such data do not exist.
When I was a deputy U.S. trade representative, I could
access reliable and nearly immediate data on trade in
goods, while the latest services trade data would be
up to a year old. Unfortunately, the services trade
data represent only a smidgeon of the total impact services
have on our economy.

A good central banker knows how
costly imperfect data can be for the economy. This is
especially true of inflation data. In late 2002 and
early 2003, for example, core PCE measurements were
indicating inflation rates that were crossing below
the 1 percent "lower boundary." At the time,
the economy was expanding in fits and starts. Given
the incidence of negative shocks during the prior two
years, the Fed was worried about the economy's ability
to withstand another one. Determined to get growth going
in this potentially deflationary environment, the FOMC
adopted an easy policy and promised to keep rates low.
A couple of years later, however, after the inflation
numbers had undergone a few revisions, we learned that
inflation had actually been a half point higher than
first thought.

In retrospect, the real fed funds
rate turned out to be lower than what was deemed appropriate
at the time and was held lower longer that it should
have been. In this case, poor data led to a policy action
that amplified speculative activity in the housing and
other markets. Today, as anybody not from the former
planet of Pluto knows, the housing market is undergoing
a substantial correction and inflicting real costs to
millions of homeowners across the country. It is complicating
the task of achieving our monetary objective of creating
the conditions for sustainable non-inflationary growth.

When we consider the potential
consequences of poor or incomplete data leading to suboptimal
policy, central bankers must be, by necessity, knights
errant of sorts, searching for the Holy Grail of economic
data that is both timely and accurate.

In this regard, I want to brag
on my team at the Dallas Fed for a minute. The Dallas
Fed has had some success at making our region's data
more timely and accurate, a significant feat when you
consider that Texas is the second most populous state,
has the fastest growing manufacturing base in the country,
grew its real output at a 9 percent rate in the first
quarter, leads the nation in exports and boasts an economic
machine larger than Korea or Brazil or Mexico and 25
percent larger than India in dollar terms.

One area of our staff's success
is with employment data. In March of each year, job
growth estimates through the preceding September are
revised using unemployment insurance records. But these
records are released quarterly, not just annually, so
we take advantage of this fact to revise our estimates
of Texas jobs on an accelerated schedule. In March 2005,
for example, the initial release put job gains for the
month at 10,600. When official revisions were released
a year later, the public found out that many new jobs
had not been counted and that the initially reported
figure was less than half the 21,700 jobs that had actually
been created. But this was something we at the Dallas
Fed already knew. Five months earlier, in August 2005,
our analysts had estimated that 17,000 jobs had been
added in March. In other words, we anticipated much
of the official revision well before it was released
seven months later. Moreover, our analysts devised a
two-step procedure for seasonally adjusting official
Texas employment data that was later adopted by the
BLS. These procedures for refining existing data help
explain why the Dallas Fed's jobs-growth forecasts consistently
outperform those of other analysts for timeliness and
accuracy.

We also have developed a measure
of inflation that is, I believe, a better predictive
tool for future price movements. The Trimmed Mean PCE
inflation rate that we calculate in Dallas looks at
monthly price movements and sets aside those price categories
that rose and fell most sharply, so that extreme swings
in the prices of individual components do not distort
our sense of the underlying trend. It does not automatically
exclude food, energy or any particular set of items.
For September, the most recent month available, our
Trimmed Mean showed inflation running at an annualized
rate of 1.7 percent, below the 2.1 percent annualized
rate registered by the ex food and energy measure of
core PCE inflation. For the past year—September
2005 to September 2006—the Trimmed Mean showed
inflation running at 2.6 percent, slightly ahead of
the ex food and energy measure of 2.4 percent.

From my perspective, the Dallas
Fed's Trimmed Mean measure is especially helpful because
it is designed to forecast the underlying trend in overall
consumer price inflation six months to a year
ahead. From the numbers I just mentioned, I draw two
conclusions. First the good news: It is possible that
the trend in overall consumer inflation has peaked and
is finally heading lower. Next, the not-so-good news:
The overall inflation trend remains at a level above
my comfort zone. I am encouraged by the change in direction
of trend inflation, and I hope that in the future my
CEO and CFO contacts will be telling me that the competitive
forces of globalization have kept their pricing power
limited or nonexistent.

So the good economists at the
Dallas Fed are making progress.

But these are relatively simple
accomplishments when we consider what is needed to maximize
our analytical efficiency in a globalized, cyber-enhanced
world. Even before we start to develop better measurement
techniques to capture the influences of new economic
entrants and technologies that continue accelerating
at the pace of Moore's Law, we first need to ask some
basic questions.

Bear with me as I present an analogy
that might strike you as a bit over the top but will,
I hope, ease us into a discussion of contemplating the
vital data we may need to inform Federal Reserve policymaking
in a dramatically changed world.

Suppose I were to create from
thin air an imaginary new currency to replace the U.S.
dollar in my home state of Texas. Since the Canadians
already have the loonie—I know how you New Yorkers
look at Texans—let's just call this new Texas
money the "burrito."

Now imagine Texas changed its
relationship to the U.S. in no other way but for the
creation of the new burrito and the establishment of
an independent central bank with responsibility solely
for Texas. The burrito would be backed by the full
faith and credit of the government in Austin, and the
Central Bank of Texas would have exactly the same mandate
as the Federal Reserve, but only for the Texas economy.

In every other way, business would
proceed as usual. No laws would change. We would stay
connected as we are now to the world around us. We would
have the same flows of goods, people, ideas and capital
that we do today as part of the United States.

How would the Central Bank of
Texas accomplish its mission? What economic indicators
would we find useful in seeking to formulate a monetary
policy designed to preserve the value of the burrito
and the sustainability of Texas' economic growth? Would
we look only within Texas' borders? Would our inflation
rate policies differ significantly from those of the
United States sans Texas? Would real Texas interest
rates be fully independent of or highly influenced—or
perhaps even determined—by U.S. rates? Would we
need to take into account the monetary policy of the
rest of the U.S. to determine our own proper monetary
stimulus or restraint?

Of course, we know that, as with
any central bank, the hypothetical Central Bank of Texas
would have the power to debase the burrito by printing
too much of it or by maladministering the central bank's
franchise. But, could we affect our employment and output,
given our real and virtual connections to the U.S. and
the world around us? If not, should we then just rewrite
our central banking mandate to focus solely on prices?
And even if we did, would we be able to make the variability
in Texas' inflation, and the corresponding inflation
risk premium, less than that of the United States? Or
would the inflationary impulses of the U.S. condition
the dynamics of Texas' inflation?

Now, let's come back to the real
world. Is it really possible to assume that like the
fictional, independent Central Bank of Texas, the Federal
Reserve can make monetary policy without taking into
account capacity constraints, levels of resource utilization,
global liquidity and other factors impacting price developments
in the rest of the world? How do we know what our true
potential growth is without properly accounting for
the world's resource potential? How can we calculate
our NAIRU without an accurate sense of workforce dynamics
and price movements outside our geographic boundaries?

Your gut-level answers to these
questions may be similar to mine. I would venture that
the Open Market Committee of a Texas central bank would
pay quite a bit of attention to economic trends in the
U.S. and the rest of the world. Reliance on Texas data
and econometric models alone would be insufficient,
perhaps even foolhardy.

The Federal Reserve has an impressive
assortment of highly sophisticated, regularly measured
and accurate data to put into its existing domestic
models. But I would argue that we need to supplement
them with data that incorporate global trends. We cannot
dismiss the worldwide resources that can be brought
to bear to increase production and the aggregate supply
of goods and services. These inputs dictate the level
of competition in the marketplace. In the real world,
developments in faraway places like China impact the
ability here at home to grow employment and profits
and to raise or lower prices. Just look at Ford Motor
Co.'s recently announced plans to cut production costs
by doubling its purchases of Chinese-made parts. Searching
the globe for better, cheaper and faster inputs is a
basic instinct of the millions of middle managers who
run supply chains for countless U.S. businesses, large
and small.

So what specific things might
we want to look at? Luckily, we do not have to look
very hard to find clues about the best answer to this
question. Looking beyond borders, as you all know, is
standard operating procedure for central banks all over
the world, including our neighbors to the north.

You know the old saw about Canada
being the vichyssoise of nations: cold, half-French
and difficult to stir. Well, the Canadians are hardly
stereotypical when it comes to making monetary policy.
In addition to looking at essential domestic and international
indicators—inflation, output gaps, GDP growth,
terms of trade, commodity prices, exchange rates, international
interest rates and so on—they begin their analysis
and estimates of the future with an outlook for global
GDP growth and global growth projections.

Canada resembles the U.S. in openness
to the world economy. But its economy is much smaller.
Indeed, Canada's output in real dollars is only a little
bit greater than Texas'. Economic theory supports the
idea that small open economies like Canada's or Texas'
have to look beyond their borders to understand inflationary
pressures because they lack the heft to influence world
prices and the capacity to be largely self-reliant.
Small economies, so the theory goes, are price takers.

Big economies like the U.S. are
price makers, and in theory, international price developments
follow our lead, thus relegating external developments
to a lesser status. Yet the euro zone nations constitute
an equally large economy. At the European Central Bank,
the very first item reviewed in its regular Monthly
Bulletin is "The External Environment of
the Euro Area." This consists of a review of real
economic developments in the U.S., Japan and the non-euro-area
OECD, as well as the U.K., other European countries,
Latin America and Asia. Next, the ECB reviews developments
in commodity markets and discusses the outlook for the
external environment. Only after looking beyond their
borders do they go into a very standard review of monetary
and financial developments in the euro area and exchange
rate and balance of payments indicators.

Here we have a big economy and
an influential central bank demonstrating the importance
of monitoring external developments along with their
domestic analysis. Maybe we can learn something from
the ECB when it comes to working global economic developments
into our deliberations.

This is not to say that the Federal
Reserve doesn't do its level best to look beyond domestic
economic indicators. We certainly do. Nor am I suggesting
that the Federal Reserve does not ultimately have the
power to control inflation in the United States. We
have it well within our grasp to debase or enhance the
value of our currency. But I would argue that international
data deserve closer examination in order to understand
the influences an integrated global economy has on our
economy and our currency and the implications of that
integration for our monetary policymaking. Last week,
my counterpart at the New York Fed, Tim Geithner, put
it this way: "Integration does not, and should
not, limit our ability to achieve our objectives. Rather,
it forces us to think harder about how our economies
are evolving and how developments in the rest of the
world affect our markets." If this is so, we have
to focus on how best to improve our collection and analysis
of global data.

The Dallas Fed is undertaking
a significant research effort to examine the issues
I've addressed today and to answer many other questions
globalization poses for the economy and for monetary
policy. To guide our research on this front, we have
put together an advisory board consisting of Martin
Feldstein, John Taylor, Ken Rogoff, Glenn Hubbard and
Nobel laureate Finn Kydland.

I will tell you one thing we have
already learned from our nascent work in Dallas and
that is that we know less about the rest of the world
than we think we do. To illustrate my point, consider
that there is no reliable measurement of the capital
stock of China. This handicaps any calculation of China's
resource utilization and invalidates any measurement
of China's "output gap." In reality, we've
no idea how much capacity exists should a gaggle of
Fords seek to cut production costs by turning to Chinese
parts suppliers.

Globalizing econometric models,
though, could help us fly a little less blindly. To
extend that metaphor, let's go back to my home base
of Texas. When I get on an airplane to fly to speak
to you here in New York, I put myself in the hands of
that plane's pilots. To carry me to LaGuardia, they
determine the best course to fly by accounting for headwinds,
tailwinds, updrafts and downdrafts in order to aeronautically
skate ahead of the puck and get us there on time and
in one piece.

Globalization brings new influences
into the Fed's navigation calculations to determine
the best flight path for the U.S. economy. To determine
that course—and to most efficiently and safely
reach our mandated destination of sustained non-inflationary
growth—we must develop a better understanding
of the new forces exerting themselves on the aircraft
we have been charged with flying. That aircraft no longer
flies solely in domestic space, affected solely by domestic
factors. Rather, it flies all over the world, requiring
more sophisticated navigation instruments to monitor
changing global and domestic economic conditions, enabling
us to pilot the craft safely and efficiently.

Herein lies the opportunity for
enterprising economists, such as yourselves, to rise
to the challenge I've presented here today and to profit
from the development of that new, sophisticated navigation
equipment. I hope you do.

I realize many of you would prefer
to discuss the more immediate outlook for the economy
and for monetary policy. So I will stop here and do
my best to not answer your questions.

Thank you.

About the Author

Richard W. Fisher is president and CEO of the Federal Reserve Bank of Dallas.

The views expressed by the author do not necessarily reflect official positions of the Federal Reserve System.